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ES4E9 - Affective Computing

  • Module code: ES4E9
  • Module name: Affective Computing
  • Department: School of Engineering
  • Credit: 15

Module content and teaching

Principal aims

Affective Computing is the inter-disciplinary study and development of systems that can recognise and interpret human affects (emotion). Information gathered from various sensors (e.g., video camera, speech detector and electroencephalogram (EEG)) are processed to recognise the appropriate affect responses. This module aims to introduce: theoretical underpinnings (psychological, physiological and technological) of affect recognition; affect sensing involving signal processing, computer vision and machine learning; and the design and implementation of effective human-machine interface applications such as health monitoring, deception detection, gaming experience and learning technologies.

 

Principal learning outcomes

By the end of the module students should be able to:

  • Integrate theories from multiple disciplines (Computer Science / Engineering / Psychology) in order to explain the main concepts of affective computing.
  • Evaluate and implement the principles of automated facial expression recognition.
  • Analyse and implement the principles of automated body language recognition.
  • Examine the principles of physiology for affective computing.
  • Critique the applications of affective computing in human-robot interactions, unobtrusive deception detection and health monitoring.